MACS: Model-based Analysis for ChIP-Seq

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Introduction

With the improvement of sequencing techniques, chromatin immunoprecipitation followed by high throughput sequencing (ChIP-Seq) is getting popular to study genome-wide protein-DNA interactions. To address the lack of powerful ChIP-Seq analysis method, we presented the Model-based Analysis of ChIP-Seq (MACS), for identifying transcript factor binding sites. MACS captures the influence of genome complexity to evaluate the significance of enriched ChIP regions and MACS improves the spatial resolution of binding sites through combining the information of both sequencing tag position and orientation. MACS can be easily used for ChIP-Seq data alone, or with a control sample with the increase of specificity. Moreover, as a general peak-caller, MACS can also be applied to any "DNA enrichment assays" if the question to be asked is simply: where we can find significant reads coverage than the random background.

Please note that current MACS3 is still in beta stage. However, we utilize Github Action to implement the CI (Continous Integration) to make sure that the main branch passes unit testing on certain functions and subcommands to reproduce the correct outputs. We will add more new features in the future.

Recent Changes for MACS (3.0.0b3)

3.0.0b3

The third beta version of MACS3, addressing Cython issue and with
two HMMRATAC options added.
   
* New features from beta2:

1) HMMRATAC module

   --modelonly option: only generate HMM model and quit
   
   -t or --training: customized training regions can be provided
   through this option.
   
   --min-frag-p: exclude fragments with abnormal fragment length while generating four
   signal tracks. #577 Check `macs3 hmmratac -h`.

2) testing for Mac OS12 is added. 

3) We require Cython 0.29.*. The new Cython3 will break our
codes. We will adopt Cython3 later. #574

Install

The common way to install MACS is through PYPI) or conda. Please check the INSTALL document for detail.

MACS3 has been tested in CI for every push and PR in the following architectures:

x86_64
aarch64
armv7
ppc64le
s390x
Apple chips

In general, you can install through PyPI as pip install macs3. To use virtual environment is highly recommended. Or you can install after unzipping the released package downloaded from Github, then use pip install . command.

Usage

Example for regular peak calling on TF ChIP-seq:

macs3 callpeak -t ChIP.bam -c Control.bam -f BAM -g hs -n test -B -q 0.01

Example for broad peak calling on Histone Mark ChIP-seq:

macs3 callpeak -t ChIP.bam -c Control.bam --broad -g hs --broad-cutoff 0.1

Example for peak calling on ATAC-seq (paired-end mode):

macs3 callpeak -f BAMPE -t ATAC.bam -g hs -n test -B -q 0.01

There are currently 14 functions available in MACS3 serving as sub-commands. Please click on the link to see the detail description of the subcommands.

Subcommand	Description
`callpeak`	Main MACS3 Function to call peaks from alignment results.
`bdgpeakcall`	Call peaks from bedGraph output.
`bdgbroadcall`	Call broad peaks from bedGraph output.
`bdgcmp`	Comparing two signal tracks in bedGraph format.
`bdgopt`	Operate the score column of bedGraph file.
`cmbreps`	Combine BEDGraphs of scores from replicates.
`bdgdiff`	Differential peak detection based on paired four bedGraph files.
`filterdup`	Remove duplicate reads, then save in BED/BEDPE format.
`predictd`	Predict d or fragment size from alignment results.
`pileup`	Pileup aligned reads (single-end) or fragments (paired-end)
`randsample`	Randomly choose a number/percentage of total reads.
`refinepeak`	Take raw reads alignment, refine peak summits.
`callvar`	Call variants in given peak regions from the alignment BAM files.
`hmmratac`	Dedicated peak calling based on Hidden Markov Model for ATAC-seq data.

For advanced usage, for example, to run macs3 in a modular way, please read the advanced usage. There is a Q&A document where we collected some common questions from users.

Contribute

Please read our CODE OF CONDUCT and How to contribute documents. If you have any questions, suggestion/ideas, or just want to have conversions with developers and other users in the community, we recommand you use the MACS Discussions instead of posting to our Issues page.

Ackowledgement

MACS3 project is sponsored by CZI EOSS. And we particularly want to thank the user community for their supports, feedbacks and contributions over the years.

yonda310/MACS